Abstract
MR measurements from an EPI sequence produce Nyquist ghost artifacts that originate from inconsistencies between odd and even echoes. By converting the ghost correction problem to an interpolation problem from uniformly down-sampled even and odd phases, here we propose a single pass reference free ghost artifact removal algorithm. Specifically, our algorithm exploits an observation that the difference between the even and odd echoes is a Fourier transform of an underlying sparse image. Accordingly, we can construct a rank-deficient Hankel structured matrix in k-space, whose missing data can be recovered using recently proposed annihilating filter-based low rank Hankel structured matrix completion approach (ALOHA). The proposed method was applied to EPI data for both single and multi-coil acquisitions. Experimental results using in-vivo data confirmed that the proposed method can completely remove ghost artifacts successfully without any pre-scan data.
| Original language | English |
|---|---|
| Title of host publication | 2016 IEEE International Symposium on Biomedical Imaging |
| Subtitle of host publication | From Nano to Macro, ISBI 2016 - Proceedings |
| Publisher | IEEE Computer Society |
| Pages | 1380-1383 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781479923502 |
| DOIs | |
| State | Published - 15 Jun 2016 |
| Event | 2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Prague, Czech Republic Duration: 13 Apr 2016 → 16 Apr 2016 |
Publication series
| Name | Proceedings - International Symposium on Biomedical Imaging |
|---|---|
| Volume | 2016-June |
| ISSN (Print) | 1945-7928 |
| ISSN (Electronic) | 1945-8452 |
Conference
| Conference | 2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 |
|---|---|
| Country/Territory | Czech Republic |
| City | Prague |
| Period | 13/04/16 → 16/04/16 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
Keywords
- EPI
- MRI
- Nyquist ghost artifact correction
- annihilating filter
- structured low rank Hankel matrix completion